Predictive Malaria Risk and Uncertainty Mapping in Nchelenge District, Zambia: Evidence of Widespread, Persistent Risk and Implications for Targeted Interventions

Abstract

Abstract. Malaria risk maps may be used to guide policy decisions on whether vector control interventions should be targeted and, if so, where. Active surveillance for malaria was conducted through household surveys in Nchelenge District, Zambia from April 2012 through December 2014. Households were enumerated based on satellite imagery and randomly selected for study enrollment. At each visit, participants were administered a questionnaire and a malaria rapid diagnostic test (RDT). Logistic regression models were used to construct spatial prediction risk maps and maps of risk uncertainty. A total of 461 households were visited, comprising 1,725 participants, of whom 48% were RDT positive. Several environmental features were associated with increased household malaria risk in a multivariable logistic regression model adjusting for seasonal variation. The model was validated using both internal and external evaluation measures to generate and assess root mean square error, as well as sensitivity and specificity for predicted risk. The final, validated model was used to predict and map malaria risk including a measure of risk uncertainty. Malaria risk in a high, perennial transmission setting is widespread but heterogeneous at a local scale, with seasonal variation. Targeting malaria control interventions may not be appropriate in this epidemiological setting.

Modeling consensus and distance to delivering indoor residual spray (IRS) implementation strategies to control malaria transmission

“…The use of global risk maps can be considered both a strength and a limitation, with data availability being one of the primary strengths. Two of the most recent malaria risk maps in Zambia were subnational, and even sub-provincial, and so would not be useful for national IRS campaigns [34,35]. These risk maps need to be validated on a larger scale before they can be useful for malaria control programs.…”

Improving the efficiency of reactive case detection for malaria elimination in southern Zambia: a cross-sectional study

“…Parents or guardians completed surveys on behalf of participants younger than sixteen years. A blood sample was collected for a PfHRP2-based RDT (SD Bioline, Standard Diagnostics Inc, Gyeonggi-do, Republic of Korea) and as dried blood spots (DBS) on Whatman 903™ Protein Saver cards (GE Healthcare Bio-Sciences Corporation, Piscataway, NJ) for quantitative PCR (qPCR) [18,19].…”

“…Neighbourhood-level risk factors included distance to the main road and distance to streams [19,23].…”

“…Studies have shown that environmental risk factors can be used to identify households likely to have parasitaemic residents [19,[20][21][22][23][24]; however, the use of such environmental risk factors have not been explored in southern Zambia in the context of RCD. Building on prior work that assessed the efficiency of RCD in southern Zambia, the predictive ability of environmental risk factors was evaluated at varied spatial scales to identify parasitaemic residents of households located within a larger radius of 250 metres from an index household [18,25,26].…”

High-Resolution Plasmodium falciparum Malaria Risk Mapping in Mutasa District, Zimbabwe: Implications for Regaining Control

“…Remote sensing data and geographic information systems have been used widely to describe spatial and temporal variations of malaria at macro and micro scales. [10][11][12][13][14] A national-level malaria risk model using district-level, monthly reported cases of malaria from health facilities across Zimbabwe found that annual and seasonal variations in malaria incidence were explained by rainfall, vapor pressure, and temperature. 15 Malaria risk zones have also been described in Masvingo Province, Zimbabwe, on the basis of eight environmental factors affecting vector reproduction, development, and survival, showing that southern districts in Masvingo Province had the highest risk of malaria.…”